Simulated tissue growth for 3D printed scaffolds

Area of Science:

• Biomaterials Science
• Tissue Engineering
• Computational Biology

Background:

• Biological tissues exhibit mechanical sensing of localized curvature, influencing growth patterns.
• Scaffold geometry is a critical factor in designing effective tissue engineering constructs.
• Understanding tissue growth dynamics on complex surfaces is essential for clinical applications.

Purpose of the Study:

• To develop a simulation approach for modeling tissue growth on beam-based scaffold geometries.
• To investigate the impact of lattice topology on tissue growth rates and patterns.
• To identify optimal scaffold designs that balance conflicting factors like growth speed and permeability.

Main Methods:

• Developed a simulation model for tissue growth on repeating unit cell geometries.
• Analyzed four distinct lattice topologies under fixed and variable geometric constraints.
• Quantified tissue growth based on positive curvature and scaffold permeability.

Main Results:

• Tissue growth preferentially occurred in voxels with positive curvature.
• Growth rates varied with lattice topology, influenced by beam density and porosity.
• Scaffolds with lower permeability showed faster tissue filling, impacting nutrient transport.
• Optimal trade-offs were identified for scaffolds with specific beam diameters and porosity.

Conclusions:

• Scaffold geometry significantly influences curvature-driven tissue growth.
• Lattice topology and porosity are key parameters for optimizing tissue scaffold design.
• Findings provide a foundation for developing advanced scaffolds for tissue regeneration.